3e2f276459f976054b5c2ab8c55be994170345da,ludwig/utils/defaults.py,,merge_with_defaults,#Any#,169

Before Change

    stratify = model_definition["preprocessing"]["stratify"]

    if stratify is not None:
        if stratify not in [x["name"] for x in
                            model_definition["output_features"]]:
            raise ValueError("Stratify must be in output features")
        if ([x for x in model_definition["output_features"] if
             x["name"] == stratify][0][TYPE]
                not in [BINARY, CATEGORY]):
            raise ValueError("Stratify feature must be binary or category")

After Change

                model_definition["input_features"] +
                model_definition["output_features"]
        )
        feature_names = set(f["name"] for f in features)
        if stratify not in feature_names:
            logger.warning(
                "Stratify is not among the features. "
                "Cannot establish if it is a binary or category"
            )
        elif ([f for f in features if f["name"] == stratify][0][TYPE]
              not in {BINARY, CATEGORY}):
            raise ValueError("Stratify feature must be binary or category")

    // ===== Training =====
    set_default_value(model_definition, TRAINING, default_training_params)

    for param, value in default_training_params.items():
        set_default_value(model_definition[TRAINING], param,

Instances